lets_plot.geom_jitter¶
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lets_plot.geom_jitter(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, width=None, height=None, **other_args)¶ Display jittered points, especially for discrete plots or dense plots.
- Parameters
mapping (FeatureSpec) – Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.
data (dict or DataFrame) – The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.
stat (str, default=’identity’) – The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).
position (str or FeatureSpec) – Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.
show_legend (bool, default=True) – False - do not show legend for this layer.
sampling (FeatureSpec) – Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.
width (float, default=0.4) – Amount of horizontal variation. The jitter is added in both directions, so the total spread is twice the specified parameter.
height (float, default=0.4) – Amount of vertical variation. The jitter is added in both directions, so the total spread is twice the specified parameter.
other_args – Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.
- Returns
Geom object specification.
- Return type
LayerSpec
Note
The jitter geometry is used to create jittered points. The scatterplot is useful for displaying the relationship between two discrete variables.
geom_jitter() understands the following aesthetics mappings:
x : x-axis value.
y : y-axis value.
alpha : transparency level of a point. Understands numbers between 0 and 1.
color (colour) : color of a geometry. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.
fill : color to paint shape’s inner points. Is applied only to the points of shapes having inner points.
shape : shape of the point.
size : size of the point.
Examples
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import numpy as np from lets_plot import * LetsPlot.setup_html() n = 1000 np.random.seed(42) x = np.random.randint(-5, 6, size=n) y = np.random.randint(10, size=n) ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \ geom_point(color='red', shape=3, size=10) + \ geom_jitter()
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import numpy as np from lets_plot import * LetsPlot.setup_html() n = 6000 np.random.seed(42) x = np.random.choice(list('abcde'), size=n) y = np.random.normal(size=n) ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \ geom_jitter(aes(color='x', size='y'), \ sampling=sampling_random(n=600, seed=60), \ show_legend=False, width=.25) + \ scale_color_grey(start=.75, end=0) + \ scale_size(range=[1, 3])